Fog-Based Delay-Sensitive Data Transmission Algorithm for Data Forwarding and Storage in Cloud Environment for Multimedia Applications.

Fog computing is playing a vital role in data transmission to distributed devices in the Internet of Things (IoT) and another network paradigm. The fundamental element of fog computing is an additional layer added between an IoT device/node and a cloud server. These fog nodes are used to speed up time-critical applications. Current research efforts and user trends are pushing for fog computing, and the path is far from being paved. Unless it can reap the benefits of applying software-defined networks and network function virtualization techniques, network monitoring will be an additional burden for fog. However, the seamless integration of these techniques in fog computing is not easy and will be a challenging task. To overcome the issues as already mentioned, the fog-based delay-sensitive data transmission algorithm develops a robust optimal technique to ensure the low and predictable delay in delay-sensitive applications such as traffic monitoring and vehicle tracking applications. The method reduces latency by storing and processing the data close to the source of information with optimal depth in the network. The deployment results show that the proposed algorithm reduces 15.67 ms round trip time and 2 seconds averaged delay on 10 KB, 100 KB, and 1 MB data set India, Singapore, and Japan Amazon Datacenter Regions compared with conventional methodologies.

Coexistence of diverse heavy metal pollution magnitudes: Health risk assessment of affected cattle and human population in some rural regions, Qena, Egypt.

OBJECTIVE: The purpose of this study was to measure the mean concentrations of heavy metals including aluminum (Al), arsenic, nickel (Ni), mercury, lead (Pb), and cadmium (Cd) and to assess the health hazards due to the exposure of cattle/human population to a distinct or the mixture of heavy metals through various sources. MATERIALS AND METHODS: A total of 180 samples including water sources, animal feed, and raw cows' milk from rural regions in Qena, Egypt, were examined using the inductively coupled plasma emission spectrometer (ICP; iCAP 6200). RESULTS: The data highlighted heavy metal pollution with variable concentrations among most of the investigated regions. All concentrations of Al, Ni, and Cd detected in the feeding stuff showed a strong correlation to their respective levels in milk rather than those detected in water (R 2= 0.072 vs. 0.039, 0.13 vs. 0.10, and 0.46 vs. 0.014, respectively) (p < 0.05). Anisocytosis and poikilocytosis with a tendency to rouleaux formation were evident, and basophilic stippling was a pathognomic indicator for heavy metal toxicity, especially Pb. Leukopenia and macrocytic anemia were shown in 50% and 65% of examined cattle, respectively. The target hazard quotients values were more than one (>1) for all heavy metals from water intake for both children and adults and Al and Cd in milk for children, and the hazard index values were indicated higher for noncarcinogenic health hazards. The target cancer risk values predispose people in the surveyed villages to higher cancerous risks due to exposures to the mixture of heavy metal through the consumption of water and milk. CONCLUSION: The bioaccumulation and transmission of heavy metal mixtures from water sources and feeding material have detrimental influences on milk pollution and cattle health which seem to be a serious issue affecting public health in those rural communities.